Allele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants (GVs) mediating post-transcriptional regulation. Recently, genome-wide detection of in vivo binding of RNA-binding proteins is greatly facilitated by the enhanced crosslinking and immunoprecipitation (eCLIP) method. We developed a new computational approach, called BEAPR, to identify allele-specific binding (ASB) events in eCLIP-Seq data. BEAPR takes into account crosslinking-induced sequence propensity and variations between replicated experiments. Using simulated and actual data, we show that BEAPR largely outperforms often-used count analysis methods. Importantly, BEAPR overcomes the inherent overdispersion problem of these methods. Complemented by experimental validations, we demonstrate that the application of BEAPR to ENCODE eCLIP-Seq data of 154 proteins helps to predict functional GVs that alter splicing or mRNA abundance. Moreover, many GVs with ASB patterns have known disease relevance. Overall, BEAPR is an effective method that helps to address the outstanding challenge of functional interpretation of GVs.

The gene encoding the core spliceosomal protein SF3B1 is the most frequently mutated gene encoding a splicing factor in a variety of hematologic malignancies and solid tumors. SF3B1 mutations induce use of cryptic 3′ splice sites (3′ss), and these splicing errors contribute to tumorigenesis. However, it is unclear how widespread this type of cryptic 3′ss usage is in cancers and what is the full spectrum of genetic mutations that cause such missplicing. To address this issue, we performed an unbiased pan-cancer analysis to identify genetic alterations that lead to the same aberrant splicing as observed with SF3B1 mutations. This analysis identified multiple mutations in another spliceosomal gene, SUGP1, that correlated with significant usage of cryptic 3′ss known to be utilized in mutant SF3B1 expressing cells. Remarkably, this is consistent with recent biochemical studies that identified a defective interaction between mutant SF3B1 and SUGP1 as the molecular defect responsible for cryptic 3′ss usage. Experimental validation revealed that five different SUGP1 mutations completely or partially recapitulated the 3′ss defects. Our analysis suggests that SUGP1 mutations in cancers can induce missplicing identical or similar to that observed in mutant SF3B1 cancers.

Pure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype–genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies.

Mutations in the core RNA splicing factor SF3B1 are prevalent in leukemias and uveal melanoma but hotspot SF3B1 mutations are also seen in epithelial malignancies such as breast cancer. Although hotspot mutations in SF3B1 alter hematopoietic differentiation, whether SF3B1 mutations contribute to epithelial cancer development and progression is unknown. Here, we identify that SF3B1 mutations in mammary epithelial and breast cancer cells induce a recurrent pattern of aberrant splicing leading to activation of AKT and NF-kB, enhanced cell migration, and accelerated tumorigenesis. Transcriptomic analysis of human cancer specimens, MMTV-cre Sf3b1 K700E/WT mice, and isogenic mutant cell lines identified hundreds of aberrant 3' splice sites (3'ss) induced by mutant SF3B1. Consistently between mouse and human tumors, mutant SF3B1 promoted aberrant splicing (dependent on aberrant branchpoints as well as pyrimidines downstream of the cryptic 3'ss) and consequent suppression of PPP2R5A and MAP3K7, critical negative regulators of AKT and NF-kB. Coordinate activation of NF-kB and AKT signaling was observed in the knock-in models, leading to accelerated cell migration and tumor development in combination with mutant PIK3CA but also hypersensitizing cells to AKT kinase inhibitors. These data identify hotspot mutations in SF3B1 as an important contributor to breast tumorigenesis and reveal unique vulnerabilities in cancers harboring them.

The common walnut (Juglans regia L.) and iron walnut (J. sigillata Dode) are well-known economically important species cultivated for their edible nuts, high-quality wood, and medicinal properties and display a sympatric distribution in southwestern China. However, detailed research on the genetic diversity and introgression of these two closely related walnut species, especially in southwestern China, are lacking. In this study, we analyzed a total of 506 individuals from 28 populations of J. regia and J. sigillata using 25 EST-SSR markers to determine if their gene introgression was related to sympatric distribution. In addition, we compared the genetic diversity estimates between them. Our results indicated that all J. regia populations possess slightly higher genetic diversity than J. sigillata populations. The Geostatistical IDW technique (HO, PPL, NA and PrA) revealed that northern Yunnan and Guizhou provinces had high genetic diversity for J. regia while the northwestern Yunnan province had high genetic diversity for J. sigillata. AMOVA analysis revealed that significant genetic variation was mainly distributed within population as 73% in J. regia and 76% in J. sigillata. The genetic differentiation (FST) was 0.307 between the two walnut species (p < 0.0001), which was higher than FST values within populations (J. regia FST = 0.265 and J. sigillata FST = 0.236). However, the STRUCTURE analysis of the J. regia and J. sigillata populations revealed two genetic clusters in which gene introgression exists, therefore, the boundary of separation between these two walnut species is not clear. Moreover, these results were validated by NJ and UPGMA analysis with additional conformation from the PCoA. Based on the SSR data, our results indicate that J. sigillata is an ecotype of J. regia. Taken together, these results reveal novel information on population genetics and provide specific geographical regions containing high genetic diversity of the Juglans species sampled, which will assist in future conservation management.